feat: Vllm reranker model bge reranker v2 m3

apps/models_provider/impl/vllm_model_provider/credential/reranker.py

@@ -0,0 +1,50 @@
+import traceback
+from typing import Dict
+
+from langchain_core.documents import Document
+
+from common import forms
+from common.exception.app_exception import AppApiException
+from common.forms import BaseForm
+from models_provider.base_model_provider import BaseModelCredential, ValidCode
+from django.utils.translation import gettext_lazy as _
+
+from models_provider.impl.vllm_model_provider.model.reranker import VllmBgeReranker
+
+
+class VllmRerankerCredential(BaseForm, BaseModelCredential):
+    api_url = forms.TextInputField('API URL', required=True)
+    api_key = forms.PasswordInputField('API Key', required=True)
+
+    def is_valid(self, model_type: str, model_name, model_credential: Dict[str, object], model_params, provider,
+                 raise_exception=True):
+        model_type_list = provider.get_model_type_list()
+        if not any(list(filter(lambda mt: mt.get('value') == model_type, model_type_list))):
+            raise AppApiException(ValidCode.valid_error.value,
+                                  _('{model_type} Model type is not supported').format(model_type=model_type))
+
+        for key in ['api_url', 'api_key']:
+            if key not in model_credential:
+                if raise_exception:
+                    raise AppApiException(ValidCode.valid_error.value, _('{key}  is required').format(key=key))
+                else:
+                    return False
+        try:
+            model: VllmBgeReranker = provider.get_model(model_type, model_name, model_credential)
+            model.compress_documents([Document(page_content=_('Hello'))], _('Hello'))
+        except Exception as e:
+            traceback.print_exc()
+            if isinstance(e, AppApiException):
+                raise e
+            if raise_exception:
+                raise AppApiException(
+                    ValidCode.valid_error.value,
+                    _('Verification failed, please check whether the parameters are correct: {error}').format(
+                        error=str(e))
+                )
+            return False
+
+        return True
+
+    def encryption_dict(self, model_info: Dict[str, object]):
+        return {**model_info, 'api_key': super().encryption(model_info.get('api_key', ''))}

apps/models_provider/impl/vllm_model_provider/model/reranker.py

@@ -0,0 +1,47 @@
+from typing import Sequence, Optional, Dict, Any
+
+import cohere
+from langchain_core.callbacks import Callbacks
+from langchain_core.documents import BaseDocumentCompressor, Document
+
+from models_provider.base_model_provider import MaxKBBaseModel
+
+
+class VllmBgeReranker(MaxKBBaseModel, BaseDocumentCompressor):
+    api_key: str
+    api_url: str
+    model: str
+    params: dict
+    client: Any = None
+
+    def __init__(self, **kwargs):
+        super().__init__(**kwargs)
+        self.api_key = kwargs.get('api_key')
+        self.model = kwargs.get('model')
+        self.params = kwargs.get('params')
+        self.api_url = kwargs.get('api_url')
+        self.client = cohere.ClientV2(kwargs.get('api_key'), base_url=kwargs.get('api_url'))
+
+    @staticmethod
+    def is_cache_model():
+        return False
+
+    @staticmethod
+    def new_instance(model_type, model_name, model_credential: Dict[str, object], **model_kwargs):
+        return VllmBgeReranker(
+            model=model_name,
+            api_key=model_credential.get('api_key'),
+            api_url=model_credential.get('api_url'),
+            params=model_kwargs,
+            **model_kwargs
+        )
+
+    def compress_documents(self, documents: Sequence[Document], query: str, callbacks: Optional[Callbacks] = None) -> \
+            Sequence[Document]:
+        if documents is None or len(documents) == 0:
+            return []
+
+        ds = [d.page_content for d in documents]
+        result = self.client.rerank(model=self.model, query=query, documents=ds)
+        return [Document(page_content=d.document.get('text'), metadata={'relevance_score': d.relevance_score}) for d in
+                result.results]

apps/models_provider/impl/vllm_model_provider/vllm_model_provider.py

@@ -10,6 +10,7 @@ from models_provider.base_model_provider import IModelProvider, ModelProvideInfo
 from models_provider.impl.vllm_model_provider.credential.embedding import VllmEmbeddingCredential
 from models_provider.impl.vllm_model_provider.credential.image import VllmImageModelCredential
 from models_provider.impl.vllm_model_provider.credential.llm import VLLMModelCredential
+from models_provider.impl.vllm_model_provider.credential.reranker import VllmRerankerCredential
 from models_provider.impl.vllm_model_provider.credential.whisper_stt import VLLMWhisperModelCredential
 from models_provider.impl.vllm_model_provider.model.embedding import VllmEmbeddingModel
 from models_provider.impl.vllm_model_provider.model.image import VllmImage
@@ -17,12 +18,14 @@ from models_provider.impl.vllm_model_provider.model.llm import VllmChatModel
 from maxkb.conf import PROJECT_DIR
 from django.utils.translation import gettext as _
 
+from models_provider.impl.vllm_model_provider.model.reranker import VllmBgeReranker
 from models_provider.impl.vllm_model_provider.model.whisper_sst import VllmWhisperSpeechToText
 
 v_llm_model_credential = VLLMModelCredential()
 image_model_credential = VllmImageModelCredential()
 embedding_model_credential = VllmEmbeddingCredential()
 whisper_model_credential = VLLMWhisperModelCredential()
+rerank_model_credential = VllmRerankerCredential()
 
 model_info_list = [
     ModelInfo('facebook/opt-125m', _('Facebook’s 125M parameter model'), ModelTypeConst.LLM, v_llm_model_credential,
@@ -50,6 +53,10 @@ whisper_model_info_list = [
     ModelInfo('whisper-large-v3', '', ModelTypeConst.STT, whisper_model_credential, VllmWhisperSpeechToText),
 ]
 
+reranker_model_info_list = [
+    ModelInfo('bge-reranker-v2-m3', '', ModelTypeConst.RERANKER, rerank_model_credential, VllmBgeReranker),
+]
+
 model_info_manage = (
     ModelInfoManage.builder()
     .append_model_info_list(model_info_list)
@@ -62,6 +69,8 @@ model_info_manage = (
     .append_default_model_info(embedding_model_info_list[0])
     .append_model_info_list(whisper_model_info_list)
     .append_default_model_info(whisper_model_info_list[0])
+    .append_model_info_list(reranker_model_info_list)
+    .append_default_model_info(reranker_model_info_list[0])
     .build()
 )
 

pyproject.toml

@@ -57,6 +57,7 @@ dependencies = [
     "python-daemon==3.1.2",
     "websockets==15.0.1",
     "pylint==3.3.7",
+    "cohere>=5.17.0",
 ]
 
 [tool.uv]